{"id":"W2132903303","doi":"10.3389/fgene.2015.00097","title":"Genomic prediction of traits related to canine hip dysplasia","year":2015,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council; Biotechnology and Biological Sciences Research Council; Medical Research Council; Scotland’s Rural College; University of Edinburgh; Sight Research UK","keywords":"Heritability; Genomic selection; Selection (genetic algorithm); Biology; Best linear unbiased prediction; Genetics; Population; Single-nucleotide polymorphism; Genotype; Medicine; Gene; Computer science; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001694019,0.0001511994,0.0001856129,0.00009741682,0.00001878583,0.000005820094,0.0002419506,0.0002020435,0.000006867078],"category_scores_gemma":[0.00005308183,0.0001651434,0.00004259961,0.0001701619,0.00007455043,0.000001625143,0.00007851191,0.00009105996,0.000005505589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003675184,"about_ca_system_score_gemma":0.0001593184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001001625,"about_ca_topic_score_gemma":0.00001345857,"domain_scores_codex":[0.9988957,0.00005764258,0.0003453657,0.0003065903,0.0001508918,0.0002437932],"domain_scores_gemma":[0.9993909,0.000003393599,0.00007364104,0.0002702545,0.00008394233,0.0001778579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005987085,0.0003332687,0.4600664,0.00006675448,0.0002455853,0.00000342306,0.003149668,0.1388172,0.2422524,0.0007180542,0.1187662,0.03498237],"study_design_scores_gemma":[0.002712135,0.002338324,0.9006457,0.00003614217,0.0000678672,0.00002414274,0.0008650828,0.0006969467,0.05204901,0.00508763,0.0350226,0.0004543895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9698147,0.002268542,0.02466874,0.00006190513,0.001051528,0.0003197345,0.00006460925,0.00001032302,0.001739966],"genre_scores_gemma":[0.8630744,0.00005930572,0.1357249,0.0000718047,0.0001045248,0.00001564143,0.00006092836,0.00002744484,0.0008610305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4405793,"threshold_uncertainty_score":0.6734353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01131650800777282,"score_gpt":0.2192548494349482,"score_spread":0.2079383414271754,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}